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python - 批量注释的 Google Vision API 问题

问题描述

我想使用 Cloud Vision API 来检测来自 ca 的标签。40K 照片并将结果下载为 CSV 文件。我将照片上传到云存储并使用以下代码，但出现错误。我问过一个在工作中使用 python 的人，但他无法处理这个错误。你能帮我修一下吗？

TypeError: Invalid constructor input for BatchAnnotateImagesRequest: [{'image': source {
  image_uri: "gs://bucket/image-path.jpg"
}
, 'features': [{'type': <Type.LABEL_DETECTION: 4>}]}]

我使用的代码：

from google.cloud import
from google.cloud import storage
from google.cloud.vision_v1 import ImageAnnotatorClient
from google.cloud.vision_v1 import types
import os
import json
import numpy as np
os.environ["GOOGLE_APPLICATION_CREDENTIALS"]='C://file-path.json'

#(created in step 1)
# Get GCS bucket
storage_client = storage.Client()
bucket = storage_client.bucket('bucket_name')
image_paths = []
for blob in list(bucket.list_blobs()):
    image_paths.append("gs://bucket_name/"+blob.name)

# We can send a maximum of 16 images per request.
start = 0
end = 16
label_output = []
for i in range(int(np.floor(len(image_paths)/16))+1):
    requests = []
    client = vision.ImageAnnotatorClient()
    for image_path in image_paths[start:end]:
        image = types.Image()
        image.source.image_uri = image_path
        requests.append({'image': image,'features': [{'type': vision.Feature.Type.LABEL_DETECTION}]})
        response = client.batch_annotate_images(requests)
    for image_path, i in zip(image_paths[start:end], response.responses):
        labels = [{label.description: label.score} for label in i.label_annotations]
        labels = {k: v for d in labels for k, v in d.items()}
        filename = os.path.basename(image_path)
        l = {'filename': filename, 'labels': labels}
        label_output.append(l)
    start = start+16
    end = end+16
#export results to CSV file
for l in label_output:
    print('"' + label_output[l]['filename'] + '";', end = '')
    for label in label_output[l]["labels"]:
        print('"' + label + '";"' + label_output[l][label] + '";', end = '')
    print("")

标签： pythonbatch-processinggoogle-cloud-vision

解决方案

batch_annotate_images()没有requests正确获取内容。要解决此问题，只需将变量requests显式requests分配给batch_annotate_images().

response = client.batch_annotate_images(requests=requests)

请参阅batch_annotate_images()以供参考。此外，如果您计划将 Vision API 更新到 2.3.1，您可能会在features:查看此参考以了解其参数的更新用法时遇到错误。

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